huggingface/text-generation-inference
5
0
Fork 0
mirror of https://github.com/huggingface/text-generation-inference.git synced 2025-09-11 12:24:53 +00:00
Code Issues Packages Projects Releases Wiki Activity

small typos

Browse Source
This commit is contained in:
moritzlaurer 2024-04-22 15:10:40 +02:00
parent 2d0a7173d4
commit bc4f42ad36
1 changed files with 4 additions and 4 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

8
docs/source/conceptual/guidance.md
View File

@ -1,6 +1,6 @@
# Guidance
Text Generation Inference (TGI) now supports [JSON and regex grammars](#grammar-and-constraints) and [tools and functions](#tools-and-functions) to help developer guide LLM responses to fit their needs.
Text Generation Inference (TGI) now supports [JSON and regex grammars](#grammar-and-constraints) and [tools and functions](#tools-and-functions) to help developers guide LLM responses to fit their needs.
These feature are available starting from version `1.4.3`. They are accessible via the [text_generation](https://pypi.org/project/text-generation/) library and is compatible with OpenAI's client libraries. The following guide will walk you through the new features and how to use them!
@ -16,7 +16,7 @@ If you're not up to date, grab the latest version and let's get started!
- [The Grammar Parameter](#the-grammar-parameter): Shape your AI's responses with precision.
- [Constrain with Pydantic](#constrain-with-pydantic): Define a grammar using Pydantic models.
- [JSON Schema Integration](#json-schema-integration): Fine grain control over your requests via JSON schema.
- [JSON Schema Integration](#json-schema-integration): Fine-grained control over your requests via JSON schema.
- [Using the client](#using-the-client): Use TGI's client libraries to shape the AI's responses.
### Tools and Functions
@ -72,9 +72,9 @@ curl localhost:3000/generate \
```
A grammar can be defined using Pydantic models, JSON schema, or regular expressions. The AI will then generate a response that conforms to the specified grammar.
A grammar can be defined using Pydantic models, JSON schemas, or regular expressions. The AI will then generate a response that conforms to the specified grammar.
> Note: A grammar must compile to a intermediate representation to constrain the output. Grammar compilation is a computationally expensive and may take a few seconds to complete on the first request. Subsequent requests will use the cached grammar and will be much faster.
> Note: A grammar must compile to an intermediate representation to constrain the output. Grammar compilation is a computationally expensive and may take a few seconds to complete on the first request. Subsequent requests will use the cached grammar and will be much faster.
### Constrain with Pydantic